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Global Optimization of Wireless Seismic Sensor Network Based on the Kriging Model and Improved Particle Swarm Optimization Algorithm

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Abstract

This study established the Kriging model to simplify the mathematical model for calculations and to improve the operational efficiency of global optimization in seismic exploration engineering. Accordingly, wireless seismic sensor network (WSSN) was used as an example in this research, and the generated seismic data flow rate and the flow rate of seismic data transmission are the simulation sample points. Thereafter, the Kriging model was constructed and the function was fitted. An improved particle swarm optimization (PSO) was also utilized for the global optimization of the Kriging model of WSSN to determine the optimized network lifetime. Results show that the Kriging model and the improved PSO algorithm significantly enhanced the lift performance and computer operational efficiency of WSSN.

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Acknowledgements

This study is supported by the National Research Foundation of China under Grant (SinoProbe-09-04, No: 201011081). The authors are very thankful to the anonymous reviewers for their constructive comments and suggestions which greatly improve the quality of this paper.

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Authors and Affiliations

  1. College of Instrumentation and Electrical Engineering, Jilin University, Changchun, China

    Xunqian Tong, Jun Lin, Yanju Ji, Guanyu Zhang & Xuefeng Xing

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  1. Xunqian Tong
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Correspondence to Guanyu Zhang.

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Tong, X., Lin, J., Ji, Y. et al. Global Optimization of Wireless Seismic Sensor Network Based on the Kriging Model and Improved Particle Swarm Optimization Algorithm. Wireless Pers Commun 95, 2203–2222 (2017). https://doi.org/10.1007/s11277-017-4051-4

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